AI Agents in Operations: What Actually Works, and What Still Does Not
A practical account of where AI agents deliver measurable value in operations-heavy businesses, where they fail, and what has to be true before you deploy one.
Read the guidePractical guides on utilization and realization, WIP and billing lag, ERP reporting, OEE, portfolio KPIs, and AI in operations. Written for the people who run project-based and industrial businesses.
A practical account of where AI agents deliver measurable value in operations-heavy businesses, where they fail, and what has to be true before you deploy one.
Read the guideEvery portfolio company reports differently, on a different cadence, with different definitions. Here is how operating partners get comparable KPIs without forcing a system migration.
OEE multiplies availability, performance, and quality into one number. Calculated weekly it is a scorecard. Calculated live it is a control system. Here is the difference.
Margin erosion is visible in the data weeks before it appears in the P&L. Here are the leading indicators worth alerting on, and how to set thresholds people will not ignore.
Procore knows what is happening on site. Sage 300 knows what it costs. Until they are joined, nobody knows project margin until closeout. Here is how contractors connect them.
Work in progress is revenue you have earned and not yet invoiced. Most project firms carry far more of it than they realize. Here is how to measure WIP age, and how to shrink it.
Vantagepoint holds the data your leadership team needs, but its native reporting was built for accountants, not operators. Here is how firms build real-time dashboards on top of it.
Utilization measures how much of your team's time is billable. Realization measures how much of that time you actually collect. Here is how to calculate both, and why firms that track only one lose margin.
An honest comparison for firms doing $20M to $500M in revenue, where the deciding factors are your existing cloud, your team's skills, and how you actually spend money.
Founder and CEO of VisualFlow Analytics. Former data analyst at Pratt & Whitney Canada, computer science and mathematics at McGill University. Leads technical delivery and client strategy across engineering, construction, and industrial data programs. Everything published here comes out of client delivery work: the metrics we are asked to define, the integrations we build, and the reporting problems that keep recurring across engineering, construction, manufacturing, and private equity operations.
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